Azure Stream Analytics is a real-time stream processing engine in the cloud that helps uncover insights from devices, sensors, infrastructure, and applications. In this session you’ll get to know this service and see it in action in some demos. Once you’ve processed your data stream, you can gain insights from it using various techniques and one of them is Machine Learning. In this session we’ll also introduce this service briefly and show how easy it for all data scientist skill levels, from setting up with only a web browser, to using drag and drop gestures and simple data flow graphs to set up experiments.

Speaker: Jan Tielens

After several years as a Microsoft Most Valuable Professional (MVP) for SharePoint Server, Jan joined Microsoft as a Technology Advisor in the collaboration and social space. Now he’s working for Microsoft as a Technical Evangelist focusing on everything related to apps for Windows, Windows Phone and Azure. Jan is located in Belgium, and you can follow him on Twitter at http://twitter.com/jantielens.

Google Cloud DataFlow

Alex Van Boxel

Google Cloud Dataflow enables reliable execution for large-scale data processing with unified programming primitives for both batch and stream-based data analysis. As a managed service, Cloud Dataflow fully manages the lifecycle of required compute resources. It can horizontally auto-scale compute resources to achieve the needed throughput level and can automatically re-shard work to optimize resource utilization.

We’ll present the open source Java-based Cloud Dataflow SDK. This SDK allows developers to benefit from the productivity of writing simple and extensible data processing pipelines that can describe both stream and batch processing tasks.

Speaker: Alex Van Boxel

Alex is a technology enthusiast and works as Software Architect at Vente-Exclusive.com. He has an R&D past at Alcatel-Lucent and Progress Software. You can follow him on twitter @alexvb or plus +AlexVanBoxel.Amazon AWS Machine Learning

Nils De Moor and Frederik Denkens

In this talk we will take a peek under the covers of Amazon Machine Learning, a new tool under the umbrella of AWS. We’ll introduce you on how to use ML to build predictive applications by finding patterns in existing data, and using these patterns to make predictions from new data as it becomes available, without having to implement custom prediction generation code or manage any infrastructure.To be completed

Speakers: Nils De Moor and Frederik Denkens

Nils is CTO at Woorank, a Belgian SaaS-startup that builds reporting tools for digital marketing agencies to follow the movement of a brand on the web and social networks. By fetching and processing millions of data points every day, he developed a passion for automating, scaling and distributing large scale applications.